Time-lapse (4D) seismic technology is the use of 3D seismic surveys acquired at different times in the productive life of a reservoir. 4D seismic can enhance asset value by increasing recovered volume and production rate, and by decreasing operating costs. 4D seismic is the only field-wide history match constraint in common use.
The most common 4D volumes used for reservoir characterization interpretation are 4D difference volumes. The difference volumes are the differences between monitor (post production) and base (often pre-production) seismic surveys. To generate difference volumes, one of the processes required is time alignment. The time alignment finds and applies the time shifts required to have seismic events on a monitor survey aligned with the corresponding events on a base survey so a meaningful difference can be taken. Time shifts themselves also contain very useful information about velocity change caused by the hydrocarbon depletions. However, they are rarely used by interpreters because the volumes are very blocky and could not be used in the same manner as difference volumes.
Time shifts are commonly used for detecting reservoir compaction and stress change in reservoir or overburden (Hudson et al. 2004, Hatchall et al. 2005, Roste et al. 2007). Production will cause the pressure decrease within the reservoir. If the pressure of the reservoir is not well maintained, compaction of the reservoir will occur, especially for younger rocks. This compaction will most likely be coupled with subsidence of the overburden and overburden dilation. The time shift data volume can be used to quantify such effects by looking at the time shifts at different time/depth levels.
In papers at the 2006 SEG meeting, Rickett et al. (2006) and Janssen et al. (2006) used time shifts to estimate the strain caused by production. Rickett shows that taking the first derivative of the time shifts enables interpreters to interpret time shifts in a manner similar to interpreting 4D difference volumes. As will be discussed later, taking a derivative of the data is an unstable operation that introduces noise into the results.
Chu and Gist (2008) used time shifts to create a low frequency model for their inverted saturation change model by calibrating the Δv/v volume with low frequency saturation change at well locations.